Abstract: In a method for an actuation of a magnetic resonance device for capturing image data from an examination region of an examination object, at least one first control sequence is provisioned, the magnetic resonance device is actuated according to the at least one first control sequence to capture first data from the examination object, the first data is analyzed with respect to a property to generate a result, and, based on the result, a selective performance of one of: a selection of a further control sequence, and termination of the actuation of the magnetic resonance device, is performed.

Abstract: In a method for generating a surrogate marker based on medical image data mapping an image region, the medical image data is detected using a first interface, a first subregion of the image region is selected by segmenting a first structure included in the image region, a first property of the first subregion is extracted, the surrogate marker is determined based on the first property, and the surrogate marker is provided using a second interface.

Abstract: Systems and methods are provided for optimizing a deep learning model. A multi-site dataset associated with different clinical sites and a deployment dataset associated with a deployment clinical site are received. A deep learning model is trained based on the multi-site dataset. The trained deep learning model is optimized based on the deployment dataset. The optimized trained deep learning model is output.

Abstract: Systems and methods for performing an assessment of a lesion are provided. A plurality of input medical images of a lesion is received. The plurality of input medical images comprises an initial input medical image and one or more additional input medical images. The initial input medical image comprises a region of interest around the lesion. A mask of the lesion is curated for the initial input medical image based on the region of interest and a set of candidate masks. The region of interest in the initial input medical image is propagated to the one or more additional input medical images based on prior registration transformations. A mask of the lesion is curated for each of the one or more additional input medical images based on the propagated regions of interest and the set of candidate masks. One or more assessments of the lesion are performed based on the mask for the initial input medical image, the masks for the one or more additional input medical images, and prior assessments of lesions.

Abstract: Systems and methods are provided for classifying an abnormality in a medical image. An input medical image depicting a lesion is received. The lesion is localized in the input medical image using a trained localization network to generate a localization map. The lesion is classified based on the input medical image and the localization map using a trained classification network. The classification of the lesion is output. The trained localization network and the trained classification network are jointly trained.

Abstract: Systems and methods are provided for classifying an abnormality in a medical image. An input medical image depicting a lesion is received. The lesion is localized in the input medical image using a trained localization network to generate a localization map. The lesion is classified based on the input medical image and the localization map using a trained classification network. The classification of the lesion is output. The trained localization network and the trained classification network are jointly trained.

Abstract: Systems and methods are provided for classifying an abnormality in a medical image. An input medical image depicting a lesion is received. The lesion is localized in the input medical image using a trained localization network to generate a localization map. The lesion is classified based on the input medical image and the localization map using a trained classification network. The classification of the lesion is output. The trained localization network and the trained classification network are jointly trained.

Abstract: Systems and methods are provided for classifying an abnormality in a medical image. An input medical image depicting a lesion is received. The lesion is localized in the input medical image using a trained localization network to generate a localization map. The lesion is classified based on the input medical image and the localization map using a trained classification network. The classification of the lesion is output. The trained localization network and the trained classification network are jointly trained.

Abstract: In a method for an actuation of a magnetic resonance device for capturing image data from an examination region of an examination object, at least one first control sequence is provisioned, the magnetic resonance device is actuated according to the at least one first control sequence to capture first data from the examination object, the first data is analyzed with respect to a property to generate a result, and, based on the result, a selective performance of one of: a selection of a further control sequence, and termination of the actuation of the magnetic resonance device, is performed.

Abstract: In a method for generating a surrogate marker based on medical image data mapping an image region, the medical image data is detected using a first interface, a first subregion of the image region is selected by segmenting a first structure included in the image region, a first property of the first subregion is extracted, the surrogate marker is determined based on the first property, and the surrogate marker is provided using a second interface.

Abstract: A treatment planning apparatus includes a treatment modeler. The treatment modeler uses models of a plurality of treatment modalities in a treatment space to generate a treatment protocol that includes one or more the modalities in the treatment space. In one implementation, a treatment modality includes the removal of targeted treatment agents from an object.

Abstract: The present embodiments relate to an MR local coil arrangement and an MR unit. An MR local coil arrangement is disclosed including at least one MR antenna, an illumination unit with at least one light-generating unit to illuminate an illumination region, and a switching unit with at least one sensor to control the illumination unit.

Abstract: The present embodiments relate to an MR local coil arrangement and an MR unit. An MR local coil arrangement is disclosed including at least one MR antenna, an illumination unit with at least one light-generating unit to illuminate an illumination region, and a switching unit with at least one sensor to control the illumination unit.

Abstract: A shape sensing device, system and method include an interventional instrument (102) having regions of articulation to be configured to change shape during an interventional procedure. An optical fiber (202) is disposed on or about the areas of articulation in a pattern to provide an optical signal indicating an instantaneous change or current position or orientation of the instrument. A signal interpretation module (115) is configured to receive the optical signals and interpret the instantaneous change or current position or orientation of the instrument.

Abstract: A treatment planning apparatus includes a treatment modeler. The treatment modeler uses models of a plurality of treatment modalities in a treatment space to generate a treatment protocol that includes one or more the modalities in the treatment space. In one implementation, a treatment modality includes the removal of targeted treatment agents from an object.

Abstract: A treatment planning apparatus (100) includes a treatment modeler (102). The treatment (104) modeler uses models (1121-N) of a plurality of treatment modalities in a treatment space (104) to generate a treatment protocol (110) that includes one or more the modalities in the treatment space. In one implementation, a treatment modality includes the removal of targeted treatment agents from an object.

Abstract: A shape sensing device, system and method include an interventional instrument (102) having regions of articulation to be configured to change shape during an interventional procedure. An optical fiber (202) is disposed on or about the areas of articulation in a pattern to provide an optical signal indicating an instantaneous change or current position or orientation of the instrument. A signal interpretation module (115) is configured to receive the optical signals and interpret the instantaneous change or cur rent position or orientation of the instrument.

Abstract: A medical device calibration apparatus, system and method include a calibration template (202) configured to position an optical shape sensing enabled interventional instrument (102). A set geometric configuration (206) is formed in or on the template to maintain the instrument in a set geometric configuration within an environment where the instrument is to be deployed. When the instrument is placed in the set geometric configuration, the instrument is calibrated for a medical procedure.

Abstract: An apparatus, method, system, computer-readable medium and use for individual patient therapy planning of diseases such as cancer for different therapy modalities, such as radiation therapy and chemotherapy is provided. A new aspect of the invention is that the degree of bone marrow depression of the patient is related to the count of immature blood platelets, which are measured before each treatment. Some embodiments of the invention provide an advantage allowing reducing the level of uncertainty in the prediction of the risk of bone marrow depression, and thus enabling to safely improve the therapy effect by an increase of the radiation dosage and/or chemical dosage to the individual patient while the risk for bone marrow depression is minimized.

Abstract: A dielectric barrier Xe discharge lamp include discharge vessel with a gas filling containing Xe or a Xe/Ne mixture and a luminescent layer of a UV-B phosphor emitting in the UV-B range 280 to 320 nm. The luminescent layer includes a Gd3+ activated phosphor according to at least one the formulas of (Y1-x-yGdxSy)Al3(BO3)4, (La1-x-yGdxSy)Al3(BO3)4, (La1-x-yGdxSy)B3O6, (Y1-x-y-zGdxSyLuz)PO4, (Y1-x-y-zGdxSyLuz)BO3, (Y1-x-y-zGdxSyLuz)3Al5O12, Me(Y1-x-yGdxSy)F4 (Me=Li, Na, K; S?Bi, Nd, Pr; 0.0<x,z?1.0; 0.0<y?0.1) or a mixture thereof. The luminescent layer may be sensitized by Bi3+, Pr3+ or Nd3+.